Some themes from rstudio::conf 2020

There were a lot of great talks at rstudio::conf. In this post I highlight a few of the themes that emerged for me.

John Blischak https://jdblischak.com
02-12-2020

Table of Contents

I had a great time last month at rstudio::conf 2020 in San Francisco. I got to catch up with my friends in the R community, make new ones, and learn about some of the latest developments for R and RStudio. Below I highlight some of the main themes from my conference experience and point to some representative talks for each one.

Disclaimer: I’ve only included talks that I saw in person. Due to space and time constraints, I wasn’t able to attend every talk I wanted to (there were 4 parallel tracks!). Also, I’ve tried to focus on talks that can be grouped into larger themes. In other words, below is a very small subset of the many great talks! For more resources, see the videos hosted by RStudio as well as the GitHub repository RStudioConf2020Slides by Emil Hvitfeldt.

My badge and hex stickers from rstudio::conf 2020.
My badge and hex stickers from rstudio::conf 2020.

Put R in production

I think one of the most exciting developments in the R community is the increasing focus on putting R in production. Instead of re-writing your R code in a different language or passing off your code to someone else to deploy, there continue to be more resources available for R users to directly deploy their applications.

Nice example from @alexkgold of deploying a machine learning model using #rstats packageshttps://t.co/AAaEjcuwrs#rstudioconf2020

— John Blischak (@jdblischak) January 29, 2020

Sage advice for putting R models in production from @heatherklus and @skyetetra:

- Avoid too many tests by only testing the most critical behavior
- Load test to find bottlenecks
- Give people a tool to explore and understand the model#rstudioconf2020

— John Blischak (@jdblischak) January 29, 2020

Also check out their great documentation on putting R in production at https://t.co/AJsO3MkRvk

— John Blischak (@jdblischak) January 29, 2020

R Markdown continues to be awesome

I’m obviously biased since I love R Markdown so much that I created an entire project framework on top of it (workflowr), but trust me that it really is awesome!

Great advice from @EmilyRiederer on using R Markdown to structure and progressively refine an analysis. If you missed her talk, check out her blog post:#rstudioconf2020https://t.co/83xCmic1RS https://t.co/i2VY94G28E

— John Blischak (@jdblischak) January 30, 2020

Parallel processing

I don’t take advantage of parallel processing nearly as often as I probably should, so it was nice to get great overview of the latest developments to make parallel code both easier to write and also more robust.

From Bryan Lewis at #rstudioconf2020: A deep dive into the foreach package to parallelize your #rstats codehttps://t.co/Q8WBvGwbRp

— John Blischak (@jdblischak) January 30, 2020

A new versatile #rstats package progressr from @henrikbengtsson for reporting progress updates #rstudioconf2020https://t.co/XTlywkb2tu

— John Blischak (@jdblischak) January 30, 2020

Programming with the tidyverse

The tidyverse packages make routine data analysis procedures much more convenient; however, I know I’m not the only one that struggles when I attempt to use non-standard evaluation inside a function. Fortunately there were multiple talks on strategies for programming with the tidyverse.

If you're using ggplot2 in your package(s), check out this guide from @paleolimbot:https://t.co/XFAYq96xIX#rstudioconf2020 https://t.co/nvn0Olilta

— John Blischak (@jdblischak) January 30, 2020

Interactivity and programming in the tidyverse. The slides of my #rstudioconf talk are available at https://t.co/vV1HXcj0vA pic.twitter.com/j8SeJzgKXB

— lionel (@_lionelhenry) January 30, 2020

Miscellaneous

Lastly, here are a few more talks I saw that I recommend.

“object of type ‘closure’ is not subsettable”
👆 is a talk I gave at #rstudioconf on getting unstuck and debugging in #rstats
Slides and other resources are here: https://t.co/9sOPBHUxRa pic.twitter.com/jzwSNpy1P2

— Jenny Bryan (@JennyBryan) January 30, 2020

Really interesting talk from @TeresaOM on predicting Mexican election results from initial polling data. They're in a “bunker” with no internet access, so no StackOverflow!#rstudioconf2020https://t.co/8Im6k6zusu

— John Blischak (@jdblischak) January 30, 2020

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Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/jdblischak/blog.jdblischak.com, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

Citation

For attribution, please cite this work as

Blischak (2020, Feb. 12). John Blischak's blog: Some themes from rstudio::conf 2020. Retrieved from https://blog.jdblischak.com/posts/rstudioconf2020/

BibTeX citation

@misc{blischak2020some,
  author = {Blischak, John},
  title = {John Blischak's blog: Some themes from rstudio::conf 2020},
  url = {https://blog.jdblischak.com/posts/rstudioconf2020/},
  year = {2020}
}

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